Figma
AI Product Research
Understanding AI Products and Their Effect on Digital Collaboration
Introduction
The collaborative landscape is constantly evolving, and the arrival of generative AI introduces a powerful new force. This project explores how teams might adapt to this "force of energy," examining how GenAI is reshaping collaborative workflows and team dynamics.
Role and Responsibilities
As a Senior Researcher at Artefact, I led the research efforts for this project to explore the impact of Generative AI on team collaboration. My responsibilities included designing the study, conducting observations and interviews, and analyzing the data, collaborating with the team to synthesize findings and contribute to the final report.
The Challenge
The primary challenge was to understand the complex and nuanced ways in which GenAI might impact team collaboration. This involved exploring both the potential benefits and drawbacks of integrating AI into collaborative workflows. The research sought to move beyond theoretical discussions and gain real-world insights into how teams interact with GenAI in practice.
The Research Process
We adopted a qualitative research approach, combining observational sessions with in-depth interviews:
- Real-World Teams: We recruited previously established teams to ensure our findings were relevant to real-world collaborative scenarios.
- Observational Sessions: Observing teams in action provided valuable insights into how GenAI tools were integrated into existing workflows and the impact on team dynamics in real-time. We recruited four teams of 3-4 individuals (designers, product managers, UX researchers, and engineers) familiar with AI tools and FigJam. Teams participated in two 45-minute ideation sessions: one without AI and one with AI (using tools Jambot and other GenAI tools like ChatGPT). We observed how teams interacted, communicated, and utilized AI during these sessions.
- In-depth Interviews: Following each observational session, we conducted 60-minute remote interviews with 1-2 team members from each team to gather their personal experiences and perspectives on using GenAI for collaboration and explore the "why" behind team behaviors and understand the subjective experiences of participants.
- Data Analysis: We analyzed the qualitative data from the observations and interviews to identify key themes and patterns related to the impact of GenAI on team dynamics, ideation processes, and overall collaboration effectiveness.
Key Insights
The research uncovered several insights into the impact of Generative AI on team collaboration:
- GenAI's Energy: GenAI can inject energy into collaborative sessions, accelerating ideation and content generation. However, this speed can also lead to a loss of "meaningful slow thinking" and create pressure on convergent moments. Teams may need to consciously balance speed with thoughtful consideration.
- Divergence and Convergence: GenAI can significantly accelerate divergence by helping teams generate a greater quantity of ideas. However, this abundance of ideas can make it more challenging to converge on a cohesive solution. Teams may need to rethink how they structure synchronous and asynchronous time to effectively manage both divergence and convergence.
- GenAI's Influence: Team members can perceive GenAI's contributions differently. Some may view AI-generated ideas as authoritative, while others treat them as mere suggestions. Teams need to establish a shared understanding of how to use AI-generated content, adopting a "fodder" mindset where AI's ideas serve as a starting point for further exploration and refinement.
- Power Dynamics: GenAI has the potential to shift power dynamics within teams. Individuals who are skilled at prompting AI or interpreting its output may exert greater influence. Teams need to establish clear norms and roles for using AI to ensure equitable participation and prevent AI-related dominance.
The Solution
To address the challenge of understanding the impact of GenAI on team collaboration, we adopted an iterative research approach, closely aligned with Figma's own product development philosophy. Recognizing that the integration of AI into collaborative workflows is an evolving process, we designed our study to not only capture current behaviors and perceptions but also to lay the groundwork for future research. The combination of observational sessions and in-depth interviews provided a rich understanding of the initial interactions between teams and GenAI, revealing key areas for exploration and refinement. This research serves as a foundation for an ongoing dialogue between Figma and its users, enabling the company to iteratively develop AI-powered collaborative tools that meet the evolving needs of teams in the future.
Results and Impact
The research report, detailing the multifaceted impact of GenAI on team collaboration, was shared with internal Figma product teams who used the insights to inform the design and development of the next generation of collaborative AI tools. Figma also hosted a webinar on our research findings, sparking discussion and interest within the design and tech communities about the future of human-AI collaboration.
Key Learnings
This project reinforced the need for human-centered research to guide the design of AI products that augment human creativity and teamwork. In future research, I would explore the long-term impact of GenAI products on team dynamics and the evolving roles of humans and AI in collaborative workflows.
Visit Figma for the full report